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Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean

Overview of attention for article published in Theoretical and Applied Genetics, November 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Title
Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean
Published in
Theoretical and Applied Genetics, November 2017
DOI 10.1007/s00122-017-3016-z
Pubmed ID
Authors

Chao Zhong, Suli Sun, Yinping Li, Canxing Duan, Zhendong Zhu

Abstract

A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.

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X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Student > Doctoral Student 3 9%
Student > Master 3 9%
Student > Postgraduate 3 9%
Researcher 3 9%
Other 3 9%
Unknown 11 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 46%
Biochemistry, Genetics and Molecular Biology 7 20%
Economics, Econometrics and Finance 1 3%
Unknown 11 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2018.
All research outputs
#4,369,510
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#588
of 3,565 outputs
Outputs of similar age
#76,182
of 327,028 outputs
Outputs of similar age from Theoretical and Applied Genetics
#19
of 51 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,565 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,028 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.